Dynamics of Heterogeneous Catalytic Processes at Operando Conditions

IF 8.5 Q1 CHEMISTRY, MULTIDISCIPLINARY
JACS Au Pub Date : 2021-11-04 DOI:10.1021/jacsau.1c00355
Xiangcheng Shi, Xiaoyun Lin, Ran Luo, Shican Wu, Lulu Li, Zhi-Jian Zhao* and Jinlong Gong*, 
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引用次数: 27

Abstract

The rational design of high-performance catalysts is hindered by the lack of knowledge of the structures of active sites and the reaction pathways under reaction conditions, which can be ideally addressed by an in situ/operando characterization. Besides the experimental insights, a theoretical investigation that simulates reaction conditions─so-called operando modeling─is necessary for a plausible understanding of a working catalyst system at the atomic scale. However, there is still a huge gap between the current widely used computational model and the concept of operando modeling, which should be achieved through multiscale computational modeling. This Perspective describes various modeling approaches and machine learning techniques that step toward operando modeling, followed by selected experimental examples that present an operando understanding in the thermo- and electrocatalytic processes. At last, the remaining challenges in this area are outlined.

Abstract Image

操作条件下非均相催化过程动力学
由于缺乏对活性位点结构和反应条件下反应途径的了解,阻碍了高性能催化剂的合理设计,而这些可以通过原位/operando表征来理想地解决。除了实验上的见解,模拟反应条件的理论研究──所谓的operando模型──对于在原子尺度上合理地理解工作中的催化剂体系也是必要的。然而,目前广泛使用的计算模型与歌剧建模的概念仍存在巨大差距,需要通过多尺度计算建模来实现。本展望描述了各种建模方法和机器学习技术,这些方法和技术都是朝着operando建模的方向发展的,其次是一些实验例子,这些例子展示了对热催化和电催化过程中operando的理解。最后,对该领域仍存在的挑战进行了概述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
9.10
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